<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.3 20210610//EN" "JATS-journalpublishing1-3.dtd">
<article article-type="research-article" dtd-version="1.3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">ntv</journal-id><journal-title-group><journal-title xml:lang="ru">Научно-технический вестник информационных технологий, механики и оптики</journal-title><trans-title-group xml:lang="en"><trans-title>Scientific and Technical Journal of Information Technologies, Mechanics and Optics</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">2226-1494</issn><issn pub-type="epub">2500-0373</issn><publisher><publisher-name>Университет ИТМО</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.17586/2226-1494-2024-24-6-923-935</article-id><article-id custom-type="elpub" pub-id-type="custom">ntv-398</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>ОПТИЧЕСКИЕ СИСТЕМЫ И ТЕХНОЛОГИИ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>OPTICAL ENGINEERING</subject></subj-group></article-categories><title-group><article-title>Современные оптические методы бесконтактных геометрических измерений и восстановления 3D-формы поверхности объектов: обзор</article-title><trans-title-group xml:lang="en"><trans-title>Modern optical methods of non-contact geometric measurements and reconstruction of object 3D surface shape: a review</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-2015-0458</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Чертов</surname><given-names>А. Н.</given-names></name><name name-style="western" xml:lang="en"><surname>Chertov</surname><given-names>A. N.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Чертов Александр Николаевич - кандидат технических наук, доцент, старший научный сотрудник,</p><p>Москва, 117342</p></bio><bio xml:lang="en"><p>Aleksandr N. Chertov - PhD, Associate Professor, Senior Researcher,</p><p>Moscow, 117342</p></bio><email xlink:type="simple">chertov.an@ntcup.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-0919-7762</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Хохлов</surname><given-names>Д. Д.</given-names></name><name name-style="western" xml:lang="en"><surname>Khokhlov</surname><given-names>D. D.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Хохлов Демид Денисович - кандидат технических наук, заведующий лабораторией,</p><p>Москва, 117342ru</p></bio><bio xml:lang="en"><p>Demid D. Khokhlov - PhD, Head of Laboratory,</p><p>Moscow, 117342</p></bio><email xlink:type="simple">khokhlov.dd@ntcup.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>Научно-технологический центр уникального приборостроения Российской академии наук</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Scientific and Technological Centre of Unique Instrumentation of the Russian Academy of Sciences</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2024</year></pub-date><pub-date pub-type="epub"><day>28</day><month>12</month><year>2024</year></pub-date><volume>24</volume><issue>6</issue><fpage>923</fpage><lpage>935</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Чертов А.Н., Хохлов Д.Д., 2024</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="ru">Чертов А.Н., Хохлов Д.Д.</copyright-holder><copyright-holder xml:lang="en">Chertov A.N., Khokhlov D.D.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://ntv.elpub.ru/jour/article/view/398">https://ntv.elpub.ru/jour/article/view/398</self-uri><abstract><sec><title>Введение</title><p>Введение. Работа посвящена изучению и систематическому обобщению существующего опыта в области определения и контроля геометрических параметров различных объектов при помощи оптических методов.</p></sec><sec><title>Метод</title><p>Метод. При поиске научных источников по тематике работы использовались открытые международные библиографические базы и поисковые машины. Для рассмотрения отбирались работы, посвященные описанию аппаратно-программных средств для бесконтактных геометрических измерений и/или восстановления 3D-формы поверхности материальных объектов, построенных на основе оптических методов, а также примеров их применения для решения практических задач. Критерием отбора рассматриваемых работ было соответствие набору ключевых слов и публикация в высокорейтинговых отечественных и зарубежных изданиях не старше 2010 года.</p></sec><sec><title>Основные результаты</title><p>Основные результаты. Предложена систематическая классификация описанных в рецензируемых научных изданиях оптических методов и аппаратно-программных средств для бесконтактных геометрических измерений и восстановления 3D-формы поверхности объектов. Выполнена сравнительная качественная оценка методов и аппаратно-программных средств. Выявлены методы, наиболее эффективные при решении отдельных практических задач. Обозначены основные ограничения рассмотренных методов и средств. Выделены основные тенденции развития рассмотренных методов. Установлено, что тенденции развития сопряжены с миниатюризацией и развитием технологий производства электронных компонентов, повышением чувствительности и увеличением пространственной и временной разрешающей способности детектирующих элементов. Также тенденции оказывают влияние на развитие методов расширения номенклатуры и функциональных возможностей источников излучения и на увеличение возможностей автоматизированной обработки данных.</p></sec><sec><title>Обсуждение</title><p>Обсуждение. Выполненный систематический обзор может быть использован при выборе оптического метода, оптимального для решения практических задач в таких областях, как неразрушающий контроль и малоинвазивная диагностика, навигация роботизированных систем, создание цифровых копий материальных объектов. Представленная работа может быть полезна студентам профильных специальностей технических учебных заведений для ознакомления с актуальным срезом современных методических и аппаратно-программных средств.</p></sec></abstract><trans-abstract xml:lang="en"><p>The article is devoted to the study and systematic generalization of the existing experience in the field of determination and control of geometric parameters of various objects using optical methods. When searching for literary sources on the work subject, open international bibliographic databases and search engines were used. Scientific articles devoted to the description of hardware and software for contactless geometric measurements and/or restoration of the threedimensional surface shape of material objects constructed on the basis of optical methods as well as examples of their application to solve practical problems were selected for consideration. The selection criterion for the works under consideration corresponded to the set of keywords and publication in highly rated domestic and foreign publications no older than 2010. A systematic classification of optical methods and hardware and software for contactless geometric measurements and restoration of the three-dimensional surface shape of objects described in peer-reviewed scientific publications is proposed, a comparative qualitative assessment is performed. The most effective methods for solving individual practical problems are identified. The main limitations of the considered methods and means are indicated. The main trends in the development of the considered methods associated with miniaturization and development of electronic component manufacturing technologies, increased sensitivity, spatial and temporal resolution of detecting elements, expanded range and functionality of radiation sources, and the development of automated data processing capabilities are highlighted. The article is a systematic review that can be used to select an optical method that is optimal for solving practical problems in such areas as non-destructive testing and minimally invasive diagnostics, navigation of robotic systems, and creation of digital copies of material objects. In addition, the presented article can be useful for students of specialized specialties of technical educational institutions to familiarize themselves with the current crosssection of modern methodological and hardware-software tools.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>измерение бесконтактное</kwd><kwd>параметр геометрический</kwd><kwd>восстановление 3D-формы</kwd><kwd>компьютерное зрение</kwd><kwd>подсветка структурированная</kwd><kwd>лазерное сканирование</kwd><kwd>компьютерная томография</kwd><kwd>система оптоволоконная изображающая</kwd><kwd>метод интерференционный</kwd></kwd-group><kwd-group xml:lang="en"><kwd>non-contact measurement</kwd><kwd>geometric parameters</kwd><kwd>3D shape recovery</kwd><kwd>computer vision</kwd><kwd>structured illumination</kwd><kwd>laser scanning</kwd><kwd>computed tomography</kwd><kwd>fiber-optic imaging system</kwd><kwd>interference method</kwd></kwd-group><funding-group><funding-statement xml:lang="ru">Работа выполнена при поддержке Министерства науки и высшего образования Российской Федерации в рамках исследовательской тематики молодежной лаборатории «Оптические зондовые приборы и методы технической и биомедицинской диагностики» (FFNS-2024-0002).</funding-statement><funding-statement xml:lang="en">This study is supported by the Ministry of Science and Higher Education of the Russian Federation (project FFNS2024-0002).</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Lu F., Wu C., Yang J. High-speed 3D shape measurement using Fourier transform and stereo vision // Journal of the European Optical Society-Rapid Publications. 2018. V. 14. N 1. P. 22. https://doi.org/10.1186/s41476-018-0090-z</mixed-citation><mixed-citation xml:lang="en">Lu F., Wu C., Yang J. High-speed 3D shape measurement using Fourier transform and stereo vision. Journal of the European Optical Society-Rapid Publications, 2018, vol. 14, no. 1, pp. 22. https://doi.org/10.1186/s41476-018-0090-z</mixed-citation></citation-alternatives></ref><ref id="cit2"><label>2</label><citation-alternatives><mixed-citation xml:lang="ru">Korotaev V.V., Pantiushin A.V., Serikova M.G., Anisimov A.G. Deflection measuring system for floating dry docks // Ocean Engineering. 2016. V. 117. P. 39–44. https://doi.org/10.1016/j. oceaneng.2016.03.012</mixed-citation><mixed-citation xml:lang="en">Korotaev V.V., Pantiushin A.V., Serikova M.G., Anisimov A.G. Deflection measuring system for floating dry docks. Ocean Engineering, 2016, vol. 117, pp. 39–44. https://doi.org/10.1016/j.oceaneng.2016.03.012</mixed-citation></citation-alternatives></ref><ref id="cit3"><label>3</label><citation-alternatives><mixed-citation xml:lang="ru">Мищенко Н.И. Трехмерные активно-импульсные системы наблюдения и измерения параметров объектов // Доклады Томского государственного университета систем управления и радиоэлектроники. 2017. Т. 20. № 3. С. 119–123. https://doi.org/10.21293/1818-0442-2017-20-3-119-123</mixed-citation><mixed-citation xml:lang="en">Mishchenko N.I. Three-dimensional active-pulse systems of observation and object parameter measurements. Proceedings of TUSUR University, 2017, vol. 20, no. 3, pp. 119–123. (in Russian). https://doi.org/10.21293/1818-0442-2017-20-3-119-123</mixed-citation></citation-alternatives></ref><ref id="cit4"><label>4</label><citation-alternatives><mixed-citation xml:lang="ru">Wu Z., Guo W., Chen Z., Wang H., Li X., Zhang Q. Three-dimensional shape and deformation measurement on complex structure parts // Scientific Reports. 2022. V. 12, pp. 7760. https://doi.org/10.1038/s41598-022-11702-x</mixed-citation><mixed-citation xml:lang="en">Wu Z., Guo W., Chen Z., Wang H., Li X., Zhang Q. Threedimensional shape and deformation measurement on complex structure parts. Scientific Reports, 2022, vol. 12, pp. 7760. https://doi.org/10.1038/s41598-022-11702-x</mixed-citation></citation-alternatives></ref><ref id="cit5"><label>5</label><citation-alternatives><mixed-citation xml:lang="ru">Pan B., Yu L., Zhang Q. Review of single-camera stereo-digital image correlation techniques for full-field 3D shape and deformation measurement // Science China Technological Sciences. 2018. V. 61. N 1. P. 2–20. https://doi.org/10.1007/s11431-017-9090-x</mixed-citation><mixed-citation xml:lang="en">Pan B., Yu L., Zhang Q. Review of single-camera stereo-digital image correlation techniques for full-field 3D shape and deformation measurement. Science China Technological Sciences, 2018, vol. 61, no. 1, pp. 2–20. https://doi.org/10.1007/s11431-017-9090-x</mixed-citation></citation-alternatives></ref><ref id="cit6"><label>6</label><citation-alternatives><mixed-citation xml:lang="ru">Ferková Z., Urbanová P., Černý D., Žuži M., Matula P. Age and gender-based human face reconstruction from single frontal image // Multimedia Tools and Applications. 2020. V. 79. N 5-6. P. 3217–3242. https://doi.org/10.1007/s11042-018-6869-5</mixed-citation><mixed-citation xml:lang="en">Ferková Z., Urbanová P., Černý D., Žuži M., Matula P. Age and gender-based human face reconstruction from single frontal image. Multimedia Tools and Applications, 2020, vol. 79, no. 5-6, pp. 3217– 3242. https://doi.org/10.1007/s11042-018-6869-5</mixed-citation></citation-alternatives></ref><ref id="cit7"><label>7</label><citation-alternatives><mixed-citation xml:lang="ru">Мурынин А.Б., Рихтер А.А. Особенности применения методов и алгоритмов реконструкции трехмерной формы ригидных объектов по данным панорамной съёмки // Машинное обучение и анализ данных. 2018. Т. 4. № 4. C. 235–247. https://doi.org/10.21469/22233792.4.4.02</mixed-citation><mixed-citation xml:lang="en">Murynin A.B., Rikhter A.A. Features of using methods and algorithms for reconstructing the three-dimensional shape of rigid objects based on panoramic photography data. Mashinnoe obuchenie i analiz dannyh, 2018, vol. 4, no. 4, pp. 235–247. https://doi.org/10.21469/22233792.4.4.02</mixed-citation></citation-alternatives></ref><ref id="cit8"><label>8</label><citation-alternatives><mixed-citation xml:lang="ru">Cui Y., Schuon S., Thrun S., Stricker D., Theobalt C. Algorithms for 3D shape scanning with a depth camera // IEEE Transactions on Pattern Analysis and Machine Intelligence. 2013. V. 35. N 5. P. 1039– 1050. https://doi.org/10.1109/TPAMI.2012.190</mixed-citation><mixed-citation xml:lang="en">Cui Y., Schuon S., Thrun S., Stricker D., Theobalt C. Algorithms for 3D shape scanning with a depth camera. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013, vol. 35, no. 5, pp. 1039–1050. https://doi.org/10.1109/TPAMI.2012.190</mixed-citation></citation-alternatives></ref><ref id="cit9"><label>9</label><citation-alternatives><mixed-citation xml:lang="ru">Онищенко С.В., Козловский А.В., Мельник Э.В. Разработка бесконтактной системы измерения геометрических параметров объектов на изображении // Известия Тульского государственного университета. Технические науки. 2022. № 9. С. 177–182. https://doi.org/10.24412/2071-6168-2022-9-177-182</mixed-citation><mixed-citation xml:lang="en">Onishchenko S.V., Kozlovsky A.V., Melnik E.V. Development of a contactless system for measuring geometric parameters of objects in the image. Izvestiya Tula State University. Technical sciences, 2022, no. 9, pp. 177–182. (in Russian). https://doi.org/10.24412/2071-6168-2022-9-177-182</mixed-citation></citation-alternatives></ref><ref id="cit10"><label>10</label><citation-alternatives><mixed-citation xml:lang="ru">Yu L., Tao R., Lubineau G. Accurate 3D shape, displacement and deformation measurement using a smartphone // Sensors. 2019. V. 19. N 3. P. 719. https://doi.org/10.3390/s19030719</mixed-citation><mixed-citation xml:lang="en">Yu L., Tao R., Lubineau G. Accurate 3D shape, displacement and deformation measurement using a smartphone. Sensors, 2019, vol. 19, no. 3, pp. 719. https://doi.org/10.3390/s19030719</mixed-citation></citation-alternatives></ref><ref id="cit11"><label>11</label><citation-alternatives><mixed-citation xml:lang="ru">Foysal K.H., Chang H.-J., Bruess F., Chong J.-W. Body size measurement using a smartphone // Electronics. 2021. V. 10. N 11. P. 1338. https://doi.org/10.3390/electronics10111338</mixed-citation><mixed-citation xml:lang="en">Foysal K.H., Chang H.-J., Bruess F., Chong J.-W. Body size measurement using a smartphone. Electronics, 2021, vol. 10, no. 11, pp. 1338. https://doi.org/10.3390/electronics10111338</mixed-citation></citation-alternatives></ref><ref id="cit12"><label>12</label><citation-alternatives><mixed-citation xml:lang="ru">Wang R., Law A.C., Garcia D., Yang S., Kong Z. Development of structured light 3D-scanner with high spatial resolution and its applications for additive manufacturing quality assurance // International Journal of Advanced Manufacturing Technology. 2021. V. 117. N 3-4. P. 845–862. https://doi.org/10.1007/s00170-021-07780- 2</mixed-citation><mixed-citation xml:lang="en">Wang R., Law A.C., Garcia D., Yang S., Kong Z. Development of structured light 3D-scanner with high spatial resolution and its applications for additive manufacturing quality assurance. International Journal of Advanced Manufacturing Technology, 2021, vol. 117, no. 3-4, pp. 845–862. https://doi.org/10.1007/s00170-021-07780-2</mixed-citation></citation-alternatives></ref><ref id="cit13"><label>13</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang S. High-speed 3D shape measurement with structured light methods: A review // Optics and Lasers in Engineering. 2018. V. 106. P. 119–131. https://doi.org/10.1016/j.optlaseng.2018.02.017</mixed-citation><mixed-citation xml:lang="en">Zhang S. High-speed 3D shape measurement with structured light methods: A review. Optics and Lasers in Engineering, 2018, vol. 106, pp. 119–131. https://doi.org/10.1016/j.optlaseng.2018.02.017</mixed-citation></citation-alternatives></ref><ref id="cit14"><label>14</label><citation-alternatives><mixed-citation xml:lang="ru">Dvoinishnikov S.V., Anikin Yu.A., Kabardin I.K., Kulikov D.V., Meledin V.G. An optoelectronic method of contactless measurement of the profile of the surface of large complexly shaped objects // Measurement Techniques. 2016. V. 59. N 1. P. 21–27. https://doi.org/10.1007/s11018-016-0910-8</mixed-citation><mixed-citation xml:lang="en">Dvoinishnikov S.V., Anikin Yu.A., Kabardin I.K., Kulikov D.V., Meledin V.G. An optoelectronic method of contactless measurement of the profile of the surface of large complexly shaped objects. Measurement Techniques, 2016, vol. 59, no. 1, pp. 21–27. https://doi.org/10.1007/s11018-016-0910-8</mixed-citation></citation-alternatives></ref><ref id="cit15"><label>15</label><citation-alternatives><mixed-citation xml:lang="ru">Kim G., Kim Y., Yun J., Moon S.-W., Kim S., Kim J., Park J., Badloe T., Kim I., Rho J. Metasurface-driven full-space structured light for three-dimensional imaging // Nature Communications. 2022. V. 13. P. 5920. https://doi.org/10.1038/s41467-022-32117-2</mixed-citation><mixed-citation xml:lang="en">Kim G., Kim Y., Yun J., Moon S.-W., Kim S., Kim J., Park J., Badloe T., Kim I., Rho J. Metasurface-driven full-space structured light for three-dimensional imaging. Nature Communications, 2022, vol. 13, pp. 5920. https://doi.org/10.1038/s41467-022-32117-2</mixed-citation></citation-alternatives></ref><ref id="cit16"><label>16</label><citation-alternatives><mixed-citation xml:lang="ru">Chen B., Shi P., Wang Y., Xu Y., Ma H., Wang R., Zheng C., Chu P. Determining surface shape of translucent objects with the combination of laser-beam-based structured light and polarization technique // Sensors. 2021. V. 21. N 19. P. 6587. https://doi.org/10.3390/s21196587</mixed-citation><mixed-citation xml:lang="en">Chen B., Shi P., Wang Y., Xu Y., Ma H., Wang R., Zheng C., Chu P. Determining surface shape of translucent objects with the combination of laser-beam-based structured light and polarization technique. Sensors, 2021, vol. 21, no. 19, pp. 6587. https://doi.org/10.3390/ s21196587</mixed-citation></citation-alternatives></ref><ref id="cit17"><label>17</label><citation-alternatives><mixed-citation xml:lang="ru">Yin W., Feng S., Tao T., Huang L., Trusiak M., Chen Q., Zuo C. Highspeed 3D shape measurement using the optimized composite fringe patterns and stereo-assisted structured light system // Optics Express. 2019. V. 27. N 3. P. 2411–2431. https://doi.org/10.1364/OE.27.002411</mixed-citation><mixed-citation xml:lang="en">Yin W., Feng S., Tao T., Huang L., Trusiak M., Chen Q., Zuo C. Highspeed 3D shape measurement using the optimized composite fringe patterns and stereo-assisted structured light system. Optics Express, 2019, vol. 27, no. 3, pp. 2411–2431. https://doi.org/10.1364/ OE.27.002411</mixed-citation></citation-alternatives></ref><ref id="cit18"><label>18</label><citation-alternatives><mixed-citation xml:lang="ru">Niu Y., Liu L., Huang F., Huang S., Chen S. Overview of image-based 3D reconstruction technology // Journal of the European Optical Society-Rapid Publications. 2024. V. 20. N 1. P. 18. https://doi.org/10.1051/jeos/2024018</mixed-citation><mixed-citation xml:lang="en">Niu Y., Liu L., Huang F., Huang S., Chen S. Overview of image-based 3D reconstruction technology. Journal of the European Optical Society-Rapid Publications, 2024, vol. 20, no. 1, pp. 18. https://doi.org/10.1051/jeos/2024018</mixed-citation></citation-alternatives></ref><ref id="cit19"><label>19</label><citation-alternatives><mixed-citation xml:lang="ru">Tang W., Jia F., Wang X. An improved adaptive triangular mesh-based image warping method // Frontiers in Neurorobotics. 2023. V. 16. P. 1042429. https://doi.org/10.3389/fnbot.2022.1042429</mixed-citation><mixed-citation xml:lang="en">Tang W., Jia F., Wang X. An improved adaptive triangular mesh-based image warping method. Frontiers in Neurorobotics, 2023, vol. 16, pp. 1042429. https://doi.org/10.3389/fnbot.2022.1042429</mixed-citation></citation-alternatives></ref><ref id="cit20"><label>20</label><citation-alternatives><mixed-citation xml:lang="ru">Клячин А.А., Клячин В.А. Алгоритм восстановления поверхности объекта по его изображению // Математическая физика и компьютерное моделирование. 2021. T. 24. № 1. С. 16–24. https://doi.org/10.15688/mpcm.jvolsu.2021.1.2</mixed-citation><mixed-citation xml:lang="en">Klyachin A.A., Klyachin V.A. Algorithm for restoring the surface of an object from its image. Mathematical Physics and Computer Simulation, 2021, vol. 24, no. 1, pp. 16–24. (in Russian). https://doi.org/10.15688/mpcm.jvolsu.2021.1.2</mixed-citation></citation-alternatives></ref><ref id="cit21"><label>21</label><citation-alternatives><mixed-citation xml:lang="ru">Шахраманьян М.А., Казарян М.Л., Рихтер А.А. Построение 3D-моделей ригидных объектов по косвенным изображениям методом координатных сеток // Информация и космос. 2018. № 3. С. 104–110.</mixed-citation><mixed-citation xml:lang="en">Shakhramanyan M., Kazaryan M., Richter A. 3D modeling of indirect image based rigid objects by applying the coordinate grid method. Information and Space, 2018, no. 3, pp. 104–110. (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit22"><label>22</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang H.M., Dong B. A review on deep learning in medical image reconstruction // Journal of the Operations Research Society of China. 2020. V. 8. N 2. P. 311–340. https://doi.org/10.1007/s40305-019-00287-4</mixed-citation><mixed-citation xml:lang="en">Zhang H.M., Dong B. A review on deep learning in medical image reconstruction. Journal of the Operations Research Society of China, 2020, vol. 8, no. 2, pp. 311–340. https://doi.org/10.1007/s40305-019-00287-4</mixed-citation></citation-alternatives></ref><ref id="cit23"><label>23</label><citation-alternatives><mixed-citation xml:lang="ru">Левашев С.П. Распознавание 3D объектов на основе спектральных инвариантов с использованием глубокого машинного обучения // Известия ЮФУ. Технические науки. 2019. № 3(205). С. 20– 31. https://doi.org/10.23683/2311-3103-2019-3-20-31</mixed-citation><mixed-citation xml:lang="en">Levashev S.P. Recognition of 3D objects based on spectral invariants using deep machine learning. Izvestiya SFedU. Engineering Sciences, 2019, no. 3(205), pp. 20–31. (in Russian). https://doi.org/10.23683/2311-3103-2019-3-20-31</mixed-citation></citation-alternatives></ref><ref id="cit24"><label>24</label><citation-alternatives><mixed-citation xml:lang="ru">Horaud R., Hansard M., Evangelidis G., Ménier C. An overview of depth cameras and range scanners based on time-of-flight technologies // Machine Vision and Applications. 2016. V. 27. N 7. P. 1005–1020. https://doi.org/10.1007/s00138-016-0784-4</mixed-citation><mixed-citation xml:lang="en">Horaud R., Hansard M., Evangelidis G., Ménier C. An overview of depth cameras and range scanners based on time-of-flight technologies. Machine Vision and Applications, 2016, vol. 27, no. 7, pp. 1005–1020. https://doi.org/10.1007/s00138-016-0784-4</mixed-citation></citation-alternatives></ref><ref id="cit25"><label>25</label><citation-alternatives><mixed-citation xml:lang="ru">Павельева Е.А. Обработка и анализ изображений на основе использования информации о фазе // Компьютерная оптика. 2018. Т. 42. № 6. С. 1022–1034. https://doi.org/10.18287/2412-6179-2018-42-6-1022-1034</mixed-citation><mixed-citation xml:lang="en">Pavelyeva E.A. Image processing and analysis based on the use of phase information. Computer Optics, 2018, vol. 42, no. 6, pp. 1022– 1034. (in Russian). https://doi.org/10.18287/2412-6179-2018-42-6-1022-1034</mixed-citation></citation-alternatives></ref><ref id="cit26"><label>26</label><citation-alternatives><mixed-citation xml:lang="ru">Shiba Y., Ono S., Furukawa R., Hiura S., Kawasaki H. Learningbased active 3D measurement technique using light field created by video projectors // IPSJ Transactions on Computer Vision and Applications. 2019. V. 11. N 1. P. 6. https://doi.org/10.1186/s41074-019-0058-y</mixed-citation><mixed-citation xml:lang="en">Shiba Y., Ono S., Furukawa R., Hiura S., Kawasaki H. Learningbased active 3D measurement technique using light field created by video projectors. IPSJ Transactions on Computer Vision and Applications, 2019, vol. 11, no. 1, pp. 6. https://doi.org/10.1186/s41074-019-0058-y</mixed-citation></citation-alternatives></ref><ref id="cit27"><label>27</label><citation-alternatives><mixed-citation xml:lang="ru">Li X., Liu Z., Cai Y., Pan C., Song J., Wang J., Shao X. Polarization 3D imaging technology: a review // Frontiers in Physics. 2023. V. 11. P. 1198457. https://doi.org/10.3389/fphy.2023.1198457</mixed-citation><mixed-citation xml:lang="en">Li X., Liu Z., Cai Y., Pan C., Song J., Wang J., Shao X. Polarization 3D imaging technology: a review. Frontiers in Physics, 2023, vol. 11, pp. 1198457. https://doi.org/10.3389/fphy.2023.1198457</mixed-citation></citation-alternatives></ref><ref id="cit28"><label>28</label><citation-alternatives><mixed-citation xml:lang="ru">Ramella-Roman J.C., Saytashev I., Piccini M. A review of polarization-based imaging technologies for clinical and preclinical applications // Journal of Optics. 2020. V. 22. N 12. P. 123001. https://doi.org/10.1088/2040-8986/abbf8a</mixed-citation><mixed-citation xml:lang="en">Ramella-Roman J.C., Saytashev I., Piccini M. A review of polarization-based imaging technologies for clinical and preclinical applications. Journal of Optics, 2020, vol. 22, no. 12, pp. 123001. https://doi.org/10.1088/2040-8986/abbf8a</mixed-citation></citation-alternatives></ref><ref id="cit29"><label>29</label><citation-alternatives><mixed-citation xml:lang="ru">Wu D., Liang Z., Chen G. Deep learning for LiDAR-only and LiDAR-fusion 3D perception: a survey // Intelligence and Robotics. 2022. V. 2. P. 105–129. https://doi.org/10.20517/ir.2021.20</mixed-citation><mixed-citation xml:lang="en">Wu D., Liang Z., Chen G. Deep learning for LiDAR-only and LiDAR-fusion 3D perception: a survey. Intelligence and Robotics, 2022, vol. 2, pp. 105–129. https://doi.org/10.20517/ir.2021.20</mixed-citation></citation-alternatives></ref><ref id="cit30"><label>30</label><citation-alternatives><mixed-citation xml:lang="ru">Li H.T., Todd Z., Bielski N., Carroll F. 3D lidar point-cloud projection operator and transfer machine learning for effective road surface features detection and segmentation // Visual Computer. 2022. V. 38. N 5. P. 1759–1774. https://doi.org/10.1007/s00371-021-02103-8</mixed-citation><mixed-citation xml:lang="en">Li H.T., Todd Z., Bielski N., Carroll F. 3D lidar point-cloud projection operator and transfer machine learning for effective road surface features detection and segmentation. Visual Computer, 2022, vol. 38, no. 5, pp. 1759–1774. https://doi.org/10.1007/s00371-021-02103-8</mixed-citation></citation-alternatives></ref><ref id="cit31"><label>31</label><citation-alternatives><mixed-citation xml:lang="ru">Di Stefano F., Chiappini S., Gorreja A., Balestra M., Pierdicca R. Mobile 3D scan LiDAR: a literature review // Geomatics, Natural Hazards and Risk. 2021. V. 12. N 1. P. 2387–2429. https://doi.org/10.1080/19475705.2021.1964617</mixed-citation><mixed-citation xml:lang="en">Di Stefano F., Chiappini S., Gorreja A., Balestra M., Pierdicca R. Mobile 3D scan LiDAR: a literature review. Geomatics, Natural Hazards and Risk, 2021, vol. 12, no. 1, pp. 2387–2429. https://doi.org/10.1080/19475705.2021.1964617</mixed-citation></citation-alternatives></ref><ref id="cit32"><label>32</label><citation-alternatives><mixed-citation xml:lang="ru">Asvadi A., Premebida C., Peixoto P., Nunes U. 3D Lidar-based static and moving obstacle detection in driving environments: An approach based on voxels and multi-region ground planes // Robotics and Autonomous Systems. 2016. V. 83. P. 299–311. https://doi.org/10.1016/J.ROBOT.2016.06.007</mixed-citation><mixed-citation xml:lang="en">Asvadi A., Premebida C., Peixoto P., Nunes U. 3D Lidar-based static and moving obstacle detection in driving environments: An approach based on voxels and multi-region ground planes. Robotics and Autonomous Systems. 2016, vol. 83, pp. 299–311. https://doi.org/10.1016/J.ROBOT.2016.06.007</mixed-citation></citation-alternatives></ref><ref id="cit33"><label>33</label><citation-alternatives><mixed-citation xml:lang="ru">Nguyen T.A., Nguyen P.T., Do S.T. Application of BIM and 3D laser scanning for quantity management in construction projects // Advances in Civil Engineering. 2020. V. 2020. https://doi.org/10.1155/2020/8839923</mixed-citation><mixed-citation xml:lang="en">Nguyen T.A., Nguyen P.T., Do S.T. Application of BIM and 3D P.T. laser scanning for quantity management in construction projects. Advances in Civil Engineering, 2020, vol. 2020. https://doi.org/10.1155/2020/8839923</mixed-citation></citation-alternatives></ref><ref id="cit34"><label>34</label><citation-alternatives><mixed-citation xml:lang="ru">Богданов А.Н., Алешутин И.А. Наземное лазерное сканирование в строительстве и BIM-технологиях // Известия Казанского государственного архитектурно-строительного университета. 2018. № 4(46). С. 326–332.</mixed-citation><mixed-citation xml:lang="en">Bogdanov A.N., Aleshutin I.A. Land laser scanning in construction and BIM-technologies. News of the Kazan State University of Architecture and Engineering, 2018, no. 4(46), pp. 326–332. (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit35"><label>35</label><citation-alternatives><mixed-citation xml:lang="ru">Рада А.О., Кузнецов А.Д., Непомнищев И.Л., Коньков Н.Ю. Совершенствование измерений объемных объектов по данным лазерного сканирования // Уголь. 2023. № 12. С. 37–43. https://doi.org/10.18796/0041-5790-2023-12-37-43</mixed-citation><mixed-citation xml:lang="en">Rada A.O., Kuznetsov A.D., Nepomnishchev I.L., Konkov N.Yu. Improving measurements of volumetric objects in the coal industry using laser scanning data. Ucol’, 2023, no. 12, pp. 37–43. (in Russian). https://doi.org/10.18796/0041-5790-2023-12-37-43</mixed-citation></citation-alternatives></ref><ref id="cit36"><label>36</label><citation-alternatives><mixed-citation xml:lang="ru">Дайнеко О. В., Калиновская Л. Ф., Бессонов Н. В. Особенности метрологического контроля бесконтактных систем измерения геометрических размеров металлопродукции // Литье и металлургия. 2021. № 1. С. 91–94. https://doi.org/10.21122/1683-6065-2021-1-91-94</mixed-citation><mixed-citation xml:lang="en">Daineko O.V., Kalinovskaya L.F., Bessonov N.V. Particularities of metrological control of non-contact systems for measuring the geometric dimensions of metal products. Foundry production and metallurgy, 2021, no. 1, pp. 91–94. (in Russian). https://doi.org/10.21122/1683-6065-2021-1-91-94</mixed-citation></citation-alternatives></ref><ref id="cit37"><label>37</label><citation-alternatives><mixed-citation xml:lang="ru">Гиря Л.В., Трофимов Г.П. Обследование памятников архитектуры с использованием современных технологий трёхмерного сканирования // Вестник Томского государственного архитектурно-строительного университета. 2022. Т. 24. № 6. С. 35−43. https://doi.org/10.31675/1607-1859-2022-24-6-35-43</mixed-citation><mixed-citation xml:lang="en">Girya L.V., Trofimov G.P. Laser 3D scanning of architectural monuments. Vestnik Tomskogo gosudarstvennogo arkhitekturnostroitel’nogo universiteta — Journal of Construction and Architecture, 2022, vol. 24, no. 6, pp. 35−43. (in Russian). https://doi.org/10.31675/1607-1859-2022-24-6-35-43</mixed-citation></citation-alternatives></ref><ref id="cit38"><label>38</label><citation-alternatives><mixed-citation xml:lang="ru">Casula G., Cuccuru F., Bianchi M.G., Fais S., Ligas P. High resolution 3-D modelling of cylinder shape bodies applied to ancient columns of a church // Advances in Geosciences. 2020. V. 54. P. 119–127. https://doi.org/10.5194/adgeo-54-119-2020</mixed-citation><mixed-citation xml:lang="en">Casula G., Cuccuru F., Bianchi M.G., Fais S., Ligas P. High resolution 3-D modelling of cylinder shape bodies applied to ancient columns of a church. Advances in Geosciences, 2020, vol. 54, pp. 119–127. https://doi.org/10.5194/adgeo-54-119-2020</mixed-citation></citation-alternatives></ref><ref id="cit39"><label>39</label><citation-alternatives><mixed-citation xml:lang="ru">Toneva D., Nikolova S., Georgiev I., Lazarov N. Impact of resolution and texture of laser scanning generated three-dimensional models on landmark identification // Anatomical Record. 2020. V. 303. N 7. P. 1950–1965. https://doi.org/10.1002/ar.24272</mixed-citation><mixed-citation xml:lang="en">Toneva D., Nikolova S., Georgiev I., Lazarov N. Impact of resolution and texture of laser scanning generated three-dimensional models on landmark identification. Anatomical Record, 2020, vol. 303, no. 7, pp. 1950–1965. https://doi.org/10.1002/ar.24272</mixed-citation></citation-alternatives></ref><ref id="cit40"><label>40</label><citation-alternatives><mixed-citation xml:lang="ru">Bhatti A.Q., Wahab A., Sindi W. An overview of 3D laser scanning techniques and application on digitization of historical structures // Innovative Infrastructure Solutions. 2021. V. 6. N 4. P. 186. https://doi.org/10.1007/s41062-021-00550-9</mixed-citation><mixed-citation xml:lang="en">Bhatti A.Q., Wahab A., Sindi W. An overview of 3D laser scanning techniques and application on digitization of historical structures. Innovative Infrastructure Solutions, 2021, vol. 6, no. 4, pp. 186. https://doi.org/10.1007/s41062-021-00550-9</mixed-citation></citation-alternatives></ref><ref id="cit41"><label>41</label><citation-alternatives><mixed-citation xml:lang="ru">Haleem A., Javaid M. 3D scanning applications in medical field: a literature-based review // Clinical Epidemiology and Global Health. 2019. V. 7. N 2. P. 199–210. https://doi.org/10.1016/j.cegh.2018.05.006</mixed-citation><mixed-citation xml:lang="en">Haleem A., Javaid M. 3D scanning applications in medical field: a literature-based review. Clinical Epidemiology and Global Health, 2019, vol. 7, no. 2, pp. 199–210. https://doi.org/10.1016/j.cegh.2018.05.006</mixed-citation></citation-alternatives></ref><ref id="cit42"><label>42</label><citation-alternatives><mixed-citation xml:lang="ru">Javaid M., Haleem A., Kumar L. Current status and applications of 3D scanning in dentistry // Clinical Epidemiology and Global Health. 2019. V. 7. N 2. P. 228–233. https://doi.org/10.1016/j.cegh.2018.07.005</mixed-citation><mixed-citation xml:lang="en">Javaid M., Haleem A., Kumar L. Current status and applications of 3D scanning in dentistry. Clinical Epidemiology and Global Health, 2019, vol. 7, no. 2, pp. 228–233. https://doi.org/10.1016/j.cegh.2018.07.005</mixed-citation></citation-alternatives></ref><ref id="cit43"><label>43</label><citation-alternatives><mixed-citation xml:lang="ru">Алтынцев М.А., Чернов А.В. Применение технологии лазерного сканирования для моделирования объектов недвижимости в 3D-кадастре // Геодезия и картография. 2018. T. 79. № 9. P. 52–63. https://doi.org/10.22389/0016-7126-2018-939-9-52-63</mixed-citation><mixed-citation xml:lang="en">Altyntsev M.A., Chernov A.V. Application of laser scanning technology for modelling real estate objects in 3D cadastre. Geodesy and Cartography, 2018, vol. 79, no. 9, pp. 52–63. (in Russian). https://doi.org/10.22389/0016-7126-2018-939-9-52-63</mixed-citation></citation-alternatives></ref><ref id="cit44"><label>44</label><citation-alternatives><mixed-citation xml:lang="ru">Hu C., Kong L., Lv F. Application of 3D laser scanning technology in engineering field // E3S Web of Conferences. 2021. V. 233. P. 04014. https://doi.org/10.1051/e3sconf/202123304014</mixed-citation><mixed-citation xml:lang="en">Hu C., Kong L., Lv F. Application of 3D laser scanning technology in engineering field. E3S Web of Conferences, 2021, vol. 233, pp. 04014. https://doi.org/10.1051/e3sconf/202123304014</mixed-citation></citation-alternatives></ref><ref id="cit45"><label>45</label><citation-alternatives><mixed-citation xml:lang="ru">Kim H., Yeo C., Cha M., Mun D. A method of generating depth images for view-based shape retrieval of 3D CAD models from partial point clouds // Multimedia Tools and Applications. 2021. V. 80. N 7. P. 10859–10880. https://doi.org/10.1007/s11042-020-10283-z</mixed-citation><mixed-citation xml:lang="en">Kim H., Yeo C., Cha M., Mun D. A method of generating depth images for view-based shape retrieval of 3D CAD models from partial point clouds. Multimedia Tools and Applications, 2021, vol. 80, no. 7, pp. 10859–10880. https://doi.org/10.1007/s11042-020-10283-z</mixed-citation></citation-alternatives></ref><ref id="cit46"><label>46</label><citation-alternatives><mixed-citation xml:lang="ru">Руденко А.В., Руденко М.А., Каширина И.Л. Алгоритмы 3D-реконструкции и расчета параметров объектов по результатам детектирования на медицинских изображениях // Моделирование, оптимизация и информационные технологии. 2024. Т. 12. № 2(45). https://doi.org/10.26102/2310-6018/2024.45.2.013</mixed-citation><mixed-citation xml:lang="en">Rudenko A.V., Rudenko M.A., Kashirina I.L. Algorithms for 3D reconstruction and calculation of object parameters based on the results of detection in medical images. Modeling, optimization and information technology, 2024, vol. 12, no. 2(45). (in Russian). https://doi.org/10.26102/2310-6018/2024.45.2.013</mixed-citation></citation-alternatives></ref><ref id="cit47"><label>47</label><citation-alternatives><mixed-citation xml:lang="ru">Лиманова Н.И., Атаев С.Г. Метод анализа снимков компьютерной томографии на основе поэтапной бинаризации изображений и его программная реализация // Информационно-управляющие системы. 2018. № 3. С. 98–106. https://doi.org/10.15217/issn1684-8853.2018.3.98</mixed-citation><mixed-citation xml:lang="en">Limanova N.I., Ataev S.G. Computer aided tomography picture analysis on the base of stage-by-stage binarization and its software implementation. Information and Control Systems, 2018, no. 3, pp. 98–106. (in Russian). https://doi.org/10.15217/issn1684-8853.2018.3.98</mixed-citation></citation-alternatives></ref><ref id="cit48"><label>48</label><citation-alternatives><mixed-citation xml:lang="ru">Kerstens A., Corthout N., Pavie B., Huang Z., Vernaillen F., Vande Velde G., Munck S. A Label-free multicolor optical surface tomography (ALMOST) imaging method for nontransparent 3D samples // BMC Biology. 2019. V. 17. N 1. P. 1. https://doi.org/10.1186/s12915-018-0614-4</mixed-citation><mixed-citation xml:lang="en">Kerstens A., Corthout N., Pavie B., Huang Z., Vernaillen F., Vande Velde G., Munck S. A Label-free multicolor optical surface tomography (ALMOST) imaging method for nontransparent 3D samples. BMC Biology, 2019, vol. 17, no. 1, pp. 1. https://doi.org/10.1186/s12915-018-0614-4</mixed-citation></citation-alternatives></ref><ref id="cit49"><label>49</label><citation-alternatives><mixed-citation xml:lang="ru">Du Z., Hu Y., Ali Buttar N., Mahmood A. X-ray computed tomography for quality inspection of agricultural products: A review // Food Science and Nutrition. 2019. V. 7. N 10. P. 3146–3160. https://doi.org/10.1002/fsn3.1179</mixed-citation><mixed-citation xml:lang="en">Du Z., Hu Y., Ali Buttar N., Mahmood A. X-ray computed tomography for quality inspection of agricultural products: A review. Food Science and Nutrition, 2019, vol. 7, no. 10, pp. 3146–3160. https://doi.org/10.1002/fsn3.1179</mixed-citation></citation-alternatives></ref><ref id="cit50"><label>50</label><citation-alternatives><mixed-citation xml:lang="ru">Zhang X., Cheng L., Liu Y., Tao B., Wang J., Liao R. A review of non-destructive methods for the detection tiny defects within organic insulating materials // Frontiers in Materials. 2022. V. 9. P. 995516. https://doi.org/10.3389/fmats.2022.995516</mixed-citation><mixed-citation xml:lang="en">Zhang X., Cheng L., Liu Y., Tao B., Wang J., Liao R. A review of non-destructive methods for the detection tiny defects within organic insulating materials. Frontiers in Materials, 2022, vol. 9, pp. 995516. https://doi.org/10.3389/fmats.2022.995516</mixed-citation></citation-alternatives></ref><ref id="cit51"><label>51</label><citation-alternatives><mixed-citation xml:lang="ru">Szabo I., Sun J., Feng G., Kanfoud J., Gan T.H., Selcuk C. Automated defect recognition as a critical element of a three dimensional X-ray computed tomography imaging-based smart non-destructive testing technique in additive manufacturing of near net-shape parts // Applied Sciences. 2017. V. 7. N 11. P. 1156. https://doi.org/10.3390/app7111156</mixed-citation><mixed-citation xml:lang="en">Szabo I., Sun J., Feng G., Kanfoud J., Gan T.H., Selcuk C. Automated defect recognition as a critical element of a three dimensional X-ray computed tomography imaging-based smart non-destructive testing technique in additive manufacturing of near net-shape parts. Applied Sciences, 2017, vol. 7, no. 11, pp. 1156. https://doi.org/10.3390/app7111156</mixed-citation></citation-alternatives></ref><ref id="cit52"><label>52</label><citation-alternatives><mixed-citation xml:lang="ru">Kastner J., Heinzl C. X-ray computed tomography for non-destructive testing and materials characterization // Integrated Imaging and Vision Techniques for Industrial Inspection: Advances and Applications. Springer, 2015. P. 227–250. https://doi.org/10.1007/978-1-4471-6741- 9_8</mixed-citation><mixed-citation xml:lang="en">Kastner J., Heinzl C. X-ray computed tomography for non-destructive testing and materials characterization. Integrated Imaging and Vision Techniques for Industrial Inspection: Advances and Applications, Springer, 2015, pp. 227–250. https://doi.org/10.1007/978-1-4471-6741-9_8</mixed-citation></citation-alternatives></ref><ref id="cit53"><label>53</label><citation-alternatives><mixed-citation xml:lang="ru">Veikutis V., Budrys T., Basevicius A., Lukosevicius S., Gleizniene R., Unikas R., Skaudickas D. Artifacts in computer tomography imaging: how it can really affect diagnostic image quality and confuse clinical diagnosis? // Journal of Vibroengineering. 2015. V. 17. N 2. P. 995– 1003.</mixed-citation><mixed-citation xml:lang="en">Veikutis V., Budrys T., Basevicius A., Lukosevicius S., Gleizniene R., Unikas R., Skaudickas D. Artifacts in computer tomography imaging: how it can really affect diagnostic image quality and confuse clinical diagnosis?. Journal of Vibroengineering, 2015, vol. 17, no. 2, pp. 995–1003.</mixed-citation></citation-alternatives></ref><ref id="cit54"><label>54</label><citation-alternatives><mixed-citation xml:lang="ru">Bauer F., Forndran D., Schromm T., Grosse C.U. Practical partspecific trajectory optimization for robot-guided inspection via computed tomography // Journal of Nondestructive Evaluation. 2022. V. 41. N 3. P. 55. https://doi.org/10.1007/s10921-022-00888-9</mixed-citation><mixed-citation xml:lang="en">Bauer F., Forndran D., Schromm T., Grosse C.U. Practical partspecific trajectory optimization for robot-guided inspection via computed tomography. Journal of Nondestructive Evaluation, 2022, vol. 41, no. 3, pp. 55. https://doi.org/10.1007/s10921-022-00888-9</mixed-citation></citation-alternatives></ref><ref id="cit55"><label>55</label><citation-alternatives><mixed-citation xml:lang="ru">He B., Zhang Y., Zhao L., Sun Z., Hu X., Kang Y., Wang L., Li Z., Huang W., Li Z., Xing G., Hua F., Wang C., Xue P., Zhang N. Robotic-OCT guided inspection and microsurgery of monolithic storage devices // Nature Communication. 2023. V.14. P. 5701. https://doi.org/10.1038/s41467-023-41498-x</mixed-citation><mixed-citation xml:lang="en">He B., Zhang Y., Zhao L., Sun Z., Hu X., Kang Y., Wang L., Li Z., Huang W., Li Z., Xing G., Hua F., Wang C., Xue P., Zhang N. Robotic-OCT guided inspection and microsurgery of monolithic storage devices. Nature Communication, 2023, vol.14, pp. 5701. https://doi.org/10.1038/s41467-023-41498-x</mixed-citation></citation-alternatives></ref><ref id="cit56"><label>56</label><citation-alternatives><mixed-citation xml:lang="ru">Smakic A., Rathmann N., Kostrzewa M., Schönberg S.O., Weiß C., Diehl S.J. Performance of a robotic assistance device in computed tomography-guided percutaneous diagnostic and therapeutic procedures // CardioVascular and Interventional Radiology. 2018. V. 41. N 4. P. 639–644. https://doi.org/10.1007/s00270-017-1841-8</mixed-citation><mixed-citation xml:lang="en">Smakic A., Rathmann N., Kostrzewa M., Schönberg S.O., Weiß C., Diehl S.J. Performance of a robotic assistance device in computed tomography-guided percutaneous diagnostic and therapeutic procedures. CardioVascular and Interventional Radiology, 2018, vol. 41, no. 4, pp. 639–644. https://doi.org/10.1007/s00270-017-1841-8</mixed-citation></citation-alternatives></ref><ref id="cit57"><label>57</label><citation-alternatives><mixed-citation xml:lang="ru">Егорова Д.А., Куликов А.В., Мухтубаев А.Б., Плотников М.Ю. Волоконно-оптическая измерительная система для определения положения и изгибов протяженных объектов в пространстве // Научно-технический вестник информационных технологий, механики и оптики. 2020. Т. 20. № 3. С. 346–352. https://doi.org/10.17586/2226-1494-2020-20-3-346-352</mixed-citation><mixed-citation xml:lang="en">Egorova D.A., Kulikov A.V., Mukhtubaev A.B., Plotnikov M.Yu. Fiber optic measurement system for determination of extended object position and bends in 3D space. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2020, vol. 20, no. 3, pp. 346–352. (in Russian). https://doi.org/10.17586/2226-1494-2020-20-3-346-352</mixed-citation></citation-alternatives></ref><ref id="cit58"><label>58</label><citation-alternatives><mixed-citation xml:lang="ru">Бутов О.В., Базакуца А.П., Чаморовский Ю.К., Федоров А.Н., Шевцов И.А. Полностью волоконный высокочувствительный датчик изгиба для атомной промышленности // Фотон-Экспресс. 2019. № 6. С. 26–27. https://doi.org/10.24411/2308-6920-2019-16008</mixed-citation><mixed-citation xml:lang="en">Butov O.V., Bazakutca A.P., Chamorovskii Iu.K., Fedorov A.N., Shevtcov I.A. All-fiber high-sensitivity bend sensor for nuclear industry. Foton-Expres, 2019, no. 6, pp. 26–27. https://doi.org/10.24411/2308-6920-2019-16008</mixed-citation></citation-alternatives></ref><ref id="cit59"><label>59</label><citation-alternatives><mixed-citation xml:lang="ru">Исламов Р.Р., Агиней Р.В., Исупова Е.В. Анализ средств и методов мониторинга напряженного состояния подземных магистральных нефтегазопроводов, работающих в сложных инже нерно-геологических условиях // Транспорт и хранение нефте продуктов и углеводородного сырья. 2017. № 6. С. 31–40.</mixed-citation><mixed-citation xml:lang="en">Islamov R.R., Aginey R.V., Isupova E.V. Analysis of ways and methods of monitoring the stressed state of underground oil and gas pipelines, working in complicated engineering-geological conditions. Transport and Storage of Oil Products and Hydrocarbons, 2017, no. 6, pp. 31–40. (in Russian)</mixed-citation></citation-alternatives></ref><ref id="cit60"><label>60</label><citation-alternatives><mixed-citation xml:lang="ru">Качура С.М., Постнов В.И. Перспективные оптоволоконные датчики и их применение (обзор) // Труды ВИАМ. 2019. № 5(77). С. 52–61. https://doi.org/10.18577/2307-6046-2019-0-5-52-61</mixed-citation><mixed-citation xml:lang="en">Kachura S.M., Postnov V.I. Perspective optical fiber sensors and their application (review). Proceedings of VIAM, 2019, no. 5(77), pp. 52– 61. (in Russian). https://doi.org/10.18577/2307-6046-2019-0-5-52-61</mixed-citation></citation-alternatives></ref><ref id="cit61"><label>61</label><citation-alternatives><mixed-citation xml:lang="ru">Di H., Xin Y., Jian J. Review of optical fiber sensors for deformation measurement // Optik. 2018. V. 168. P. 703–713. https://doi.org/10.1016/j.ijleo.2018.04.131</mixed-citation><mixed-citation xml:lang="en">Di H., Xin Y., Jian J. Review of optical fiber sensors for deformation measurement. Optik, 2018, vol. 168, pp. 703–713. https://doi.org/10.1016/j.ijleo.2018.04.131</mixed-citation></citation-alternatives></ref><ref id="cit62"><label>62</label><citation-alternatives><mixed-citation xml:lang="ru">Fröch J.E., Huang L., Tanguy Q.A., Colburn S., Zhan A., Ravagli A., Seibel E.J., Böhringer K.F., Majumdar A. Real time full-color imaging in a Meta-optical fiber endoscope // eLight. 2023. V. 3. N 1. P. 13. https://doi.org/10.1186/s43593-023-00044-4</mixed-citation><mixed-citation xml:lang="en">Fröch J.E., Huang L., Tanguy Q.A., Colburn S., Zhan A., Ravagli A., Seibel E.J., Böhringer K.F., Majumdar A. Real time full-color imaging in a Meta-optical fiber endoscope. eLight, 2023, vol. 3, no. 1, pp. 13. https://doi.org/10.1186/s43593-023-00044-4</mixed-citation></citation-alternatives></ref><ref id="cit63"><label>63</label><citation-alternatives><mixed-citation xml:lang="ru">Belinsky A.V., Gostev P.P., Magnitskiy S.A., Chirkin A.S. Ghost fiber optic 3D endoscopy // JETP Letters. 2023. V. 117. N 3. P. 202–206. https://doi.org/10.1134/S0021364022602718</mixed-citation><mixed-citation xml:lang="en">Belinsky A.V., Gostev P.P., Magnitskiy S.A., Chirkin A.S. Ghost fiber optic 3D endoscopy. JETP Letters, 2023, vol. 117, no. 3, pp. 202–206. https://doi.org/10.1134/S0021364022602718</mixed-citation></citation-alternatives></ref><ref id="cit64"><label>64</label><citation-alternatives><mixed-citation xml:lang="ru">Peng X., Kong L. Design of a real-time fiber-optic infrared imaging system with wide-angle and large depth of field // Chinese Optics Letters. 2022. V. 20. N 1. P. 011201. https://doi.org/10.3788/COL202220.011201</mixed-citation><mixed-citation xml:lang="en">Peng X., Kong L. Design of a real-time fiber-optic infrared imaging system with wide-angle and large depth of field. Chinese Optics Letters, 2022, vol. 20, no. 1, pp. 011201. https://doi.org/10.3788/COL202220.011201</mixed-citation></citation-alternatives></ref><ref id="cit65"><label>65</label><citation-alternatives><mixed-citation xml:lang="ru">Amitonova L.V. Multimode fiber endoscopes for computational brain imaging // Neurophotonics. 2024. V. 11. N S1. P. S11509. https://doi.org/10.1117/1.NPh.11.S1.S11509</mixed-citation><mixed-citation xml:lang="en">Amitonova L.V. Multimode fiber endoscopes for computational brain imaging. Neurophotonics, 2024, vol. 11, no. S1, pp. S11509. https://doi.org/10.1117/1.NPh.11.S1.S11509</mixed-citation></citation-alternatives></ref><ref id="cit66"><label>66</label><citation-alternatives><mixed-citation xml:lang="ru">Stellinga D., Phillips D.B., Mekhail S.P., Selyem A., Turtaev S., Čižmár T., Padgett M.J. Time-of-flight 3D imaging through multimode optical fibers // Science. 2021. V. 374. N 6573. P. 1395– 1399. https://doi.org/10.1126/science.abl3771</mixed-citation><mixed-citation xml:lang="en">Stellinga D., Phillips D.B., Mekhail S.P., Selyem A., Turtaev S., Čižmár T., Padgett M.J. Time-of-flight 3D imaging through multimode optical fibers. Science, 2021, vol. 374, no. 6573, pp. 1395– 1399. https://doi.org/10.1126/science.abl3771</mixed-citation></citation-alternatives></ref><ref id="cit67"><label>67</label><citation-alternatives><mixed-citation xml:lang="ru">Caramazza P., Moran O., Murray-Smith R., Faccio D. Transmission of natural scene images through a multimode fibre // Nature Communications. 2019. V. 10. P. 2029. https://doi.org/10.1038/s41467-019-10057-8</mixed-citation><mixed-citation xml:lang="en">Caramazza P., Moran O., Murray-Smith R., Faccio D. Transmission of natural scene images through a multimode fibre. Nature Communications, 2019, vol. 10, pp. 2029. https://doi.org/10.1038/s41467-019-10057-8</mixed-citation></citation-alternatives></ref><ref id="cit68"><label>68</label><citation-alternatives><mixed-citation xml:lang="ru">Rahmani B., Oguz I., Tegin U., Hsieh J., Psaltis D., Moser C. Learning to image and compute with multimode optical fibers // Nanophotonics. 2022. V. 11. N 6. P. 1071–1082. https://doi.org/10.1515/nanoph-2021-0601</mixed-citation><mixed-citation xml:lang="en">Rahmani B., Oguz I., Tegin U., Hsieh J., Psaltis D., Moser C. Learning to image and compute with multimode optical fibers. Nanophotonics, 2022, vol. 11, no. 6, pp. 1071–1082. https://doi.org/10.1515/nanoph-2021-0601</mixed-citation></citation-alternatives></ref><ref id="cit69"><label>69</label><citation-alternatives><mixed-citation xml:lang="ru">Wang L., Qi T., Liu Z., Meng Y., Li D., Yan P., Gong M., Xiao Q. Complex pattern transmission through multimode fiber under diverse light sources // APL Photonics. 2022. V. 7. N 10. P. 106104. https://doi.org/10.1063/5.0098370</mixed-citation><mixed-citation xml:lang="en">Wang L., Qi T., Liu Z., Meng Y., Li D., Yan P., Gong M., Xiao Q. Complex pattern transmission through multimode fiber under diverse light sources. APL Photonics, 2022, vol. 7, no. 10, pp. 106104. https://doi.org/10.1063/5.0098370</mixed-citation></citation-alternatives></ref><ref id="cit70"><label>70</label><citation-alternatives><mixed-citation xml:lang="ru">Xin L., Liu X., Yang Z., Zhang X., Gao Z., Liu Z. Three-dimensional reconstruction of super-resolved white-light interferograms based on deep learning // Optics and Lasers in Engineering. 2021. V. 145. P. 106663. https://doi.org/10.1016/j.optlaseng.2021.106663</mixed-citation><mixed-citation xml:lang="en">Xin L., Liu X., Yang Z., Zhang X., Gao Z., Liu Z. Three-dimensional reconstruction of super-resolved white-light interferograms based on deep learning. Optics and Lasers in Engineering, 2021, vol. 145, pp. 106663. https://doi.org/10.1016/j.optlaseng.2021.106663</mixed-citation></citation-alternatives></ref><ref id="cit71"><label>71</label><citation-alternatives><mixed-citation xml:lang="ru">Osten W., Pedrini G. 55 years of holographic non-destructive testing and experimental stress analysis: is there still progress to be expected? // Light: Advanced Manufacturing. 2022. V. 3. N 1. P. 121– 136. https://doi.org/10.37188/lam.2022.008</mixed-citation><mixed-citation xml:lang="en">Osten W., Pedrini G. 55 years of holographic non-destructive testing and experimental stress analysis: is there still progress to be expected?. Light: Advanced Manufacturing, 2022, vol. 3, no. 1, pp. 121–136. https://doi.org/10.37188/lam.2022.008</mixed-citation></citation-alternatives></ref><ref id="cit72"><label>72</label><citation-alternatives><mixed-citation xml:lang="ru">Petrov V., Pogoda A., Sementin V., Sevryugin A., Shalymov E., Venediktov D., Venediktov V. Advances in digital holographic interferometry // Journal of Imaging. 2022. V. 8. N 7. P. 196. https://doi.org/10.3390/jimaging8070196</mixed-citation><mixed-citation xml:lang="en">Petrov V., Pogoda A., Sementin V., Sevryugin A., Shalymov E., Venediktov D., Venediktov V. Advances in digital holographic interferometry. Journal of Imaging, 2022, vol. 8, no. 7, pp. 196. https://doi.org/10.3390/jimaging8070196</mixed-citation></citation-alternatives></ref><ref id="cit73"><label>73</label><citation-alternatives><mixed-citation xml:lang="ru">Javidi B., Carnicer A., Anand A., Barbastathis G., Chen W., Ferraro P., Goodman J.W., Horisaki R., Khare K., Kujawinska M., Leitgeb R.A., Marquet P., Nomura T., Ozcan A., Park Y., Pedrini G., Picart P., Rosen J., Saavedra G., Shaked N.T., Stern A., Tajahuerce E., Tian L., Wetzstein G., Yamaguchi M. Roadmap on digital holography // Optics Express. 2021. V. 29. N 22. P. 35078–35118. https://doi.org/10.1364/OE.435915</mixed-citation><mixed-citation xml:lang="en">Javidi B., Carnicer A., Anand A., Barbastathis G., Chen W., Ferraro P., Goodman J.W., Horisaki R., Khare K., Kujawinska M., Leitgeb R.A., Marquet P., Nomura T., Ozcan A., Park Y., Pedrini G., Picart P., Rosen J., Saavedra G., Shaked N.T., Stern A., Tajahuerce E., Tian L., Wetzstein G., Yamaguchi M. Roadmap on digital holography. Optics Express, 2021, vol. 29, no. 22, pp. 35078–35118. https://doi.org/10.1364/OE.435915</mixed-citation></citation-alternatives></ref><ref id="cit74"><label>74</label><citation-alternatives><mixed-citation xml:lang="ru">Behal J., Memmolo P., Miccio L., Bianco V., Ferraro P. On the optical performance of incoherent digital holography for extended 3D objects // Optics &amp; Laser Technology. 2024. V. 170. P. 110286. https://doi.org/10.1016/j.optlastec.2023.110286</mixed-citation><mixed-citation xml:lang="en">Behal J., Memmolo P., Miccio L., Bianco V., Ferraro P. On the optical performance of incoherent digital holography for extended 3D objects. Optics &amp; Laser Technology, 2024, vol. 170, pp. 110286. https://doi.org/10.1016/j.optlastec.2023.110286</mixed-citation></citation-alternatives></ref><ref id="cit75"><label>75</label><citation-alternatives><mixed-citation xml:lang="ru">Tahara T. Review of incoherent digital holography: applications to multidimensional incoherent digital holographic microscopy and palm-sized digital holographic recorder–holosensor // Frontiers in Photonics. 2022. V. 2. https://doi.org/10.3389/fphot.2021.829139</mixed-citation><mixed-citation xml:lang="en">Tahara T. Review of incoherent digital holography: applications to multidimensional incoherent digital holographic microscopy and palm-sized digital holographic recorder–holosensor. Frontiers in Photonics, 2022, vol. 2. https://doi.org/10.3389/fphot.2021.829139</mixed-citation></citation-alternatives></ref><ref id="cit76"><label>76</label><citation-alternatives><mixed-citation xml:lang="ru">Zeppieri M., Marsili S., Enaholo E.S., Shuaibu A.O., Uwagboe N., Salati C., Spadea L., Musa M. Optical coherence tomography (OCT): A brief look at the uses and technological evolution of ophthalmology // Medicina. 2023. V. 59. N 12. P. 2114. https://doi.org/10.3390/medicina59122114</mixed-citation><mixed-citation xml:lang="en">Zeppieri M., Marsili S., Enaholo E.S., Shuaibu A.O., Uwagboe N., Salati C., Spadea L., Musa M. Optical coherence tomography (OCT): A brief look at the uses and technological evolution of ophthalmology. Medicina, 2023, vol. 59, no. 12, pp. 2114. https://doi.org/10.3390/medicina59122114</mixed-citation></citation-alternatives></ref><ref id="cit77"><label>77</label><citation-alternatives><mixed-citation xml:lang="ru">Zheng S., Bai Y., Xu Z., Liu P., Ni G. Optical coherence tomography for three-dimensional imaging in the biomedical field: A review // Frontiers in Physics. 2021. V. 9. https://doi.org/10.3389/fphy.2021.744346</mixed-citation><mixed-citation xml:lang="en">Zheng S., Bai Y., Xu Z., Liu P., Ni G. Optical coherence tomography for three-dimensional imaging in the biomedical field: A review. Frontiers in Physics, 2021, vol. 9. https://doi.org/10.3389/fphy.2021.744346</mixed-citation></citation-alternatives></ref><ref id="cit78"><label>78</label><citation-alternatives><mixed-citation xml:lang="ru">Koponen A., Haavisto S. Analysis of industry-related flows by optical coherence tomography – a review // KONA Powder and Particle Journal. 2020. V. 37. P. 42–63. https://doi.org/10.14356/kona.2020003</mixed-citation><mixed-citation xml:lang="en">Koponen A., Haavisto S. Analysis of industry-related flows by optical coherence tomography — a review. KONA Powder and Particle Journal, 2020, vol. 37, pp. 42–63. https://doi.org/10.14356/kona.2020003</mixed-citation></citation-alternatives></ref></ref-list><fn-group><fn fn-type="conflict"><p>The authors declare that there are no conflicts of interest present.</p></fn></fn-group></back></article>
